Identification of Three Significant Genes Associated with Immune Cells Infiltration in Dysfunctional Adipose Tissue-Induced Insulin-Resistance of Obese Patients via Comprehensive Bioinformatics Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33564304", "kind": "science-record", "revision": 8, "content_hash": "sha256:2a74580f613485efe57f661b8bc0f67bfe4f4e71e5ce723ccc6dbbba4963be38", "created_at": "2026-11-01T15:41:24Z", "updated_at": "2026-11-01T22:46:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Three Significant Genes Associated with Immune Cells Infiltration in Dysfunctional Adipose Tissue-Induced Insulin-Resistance of Obese Patients via Comprehensive Bioinformatics Analysis.", "doi": "10.1155/2021/8820089", "pmid": "33564304", "authors": ["Ming Zhai", "Peipei Luan", "Yefei Shi", "Bo Li", "Jianhua Kang", "Fan Hu", "Mingjie Li", "Lei Du", "Donglei Zhou", "Weixia Jian", "Wenhui Peng"], "journal": "International journal of endocrinology", "year": 2021, "abstract": "BACKGROUND: Low-grade chronic inflammation in dysfunctional adipose tissue links obesity with insulin resistance through the activation of tissue-infiltrating immune cells. Numerous studies have reported on the pathogenesis of insulin-resistance. However, few studies focused on genes from genomic database. In this study, we would like to explore the correlation of genes and immune cells infiltration in adipose tissue via comprehensive bioinformatics analyses and experimental validation in mice and human adipose tissue.\nMETHODS: Gene Expression Omnibus (GEO) datasets (GSE27951, GSE55200, and GSE26637) of insulin-resistant individuals or type 2 diabetes patients and normal controls were downloaded to get differently expressed genes (DEGs), and GO and KEGG pathway analyses were performed. Subsequently, we integrated DEGs from three datasets and constructed commonly expressed DEGs' PPI net-works across datasets. Center regulating module of DEGs and hub genes were screened through MCODE and cytoHubba in Cytoscape. Three most significant hub genes were further analyzed by GSEA analysis. Moreover, we verified the predicted hub genes by performing RT qPCR analysis in animals and human samples. Besides, the relative fraction of 22 immune cell types in adipose tissue was detected by using the deconvolution algorithm of CIBERSORT (Cell Type Identification by Estimating Relative Subsets of RNA Transcripts). Furthermore, based on the significantly changed types of immune cells, we performed correlation analysis between hub genes and immune cells. And, we performed immunohistochemistry and immunofluorescence analysis to verify that the hub genes were associated with adipose tissue macrophages (ATM).\nRESULTS: Thirty DEGs were commonly expressed across three datasets, most of which were upregulated. DEGs mainly participated in the process of multiple immune cells' infiltration. In protein-protein interaction network, we identified CSF1R, C1QC, and TYROBP as hub genes. GSEA analysis suggested high expression of the three hub genes was correlated with immune cells functional pathway's activation. Immune cell infiltration and correlation analysis revealed that there were significant positive correlations between TYROBP and M0 macrophages, CSF1R and M0 macrophages, Plasma cells, and CD8 T cells. Finally, hub genes were associated with ATMs infiltration by experimental verification.\nCONCLUSIONS: This article revealed that CSF1R, C1QC, and TYROBP were potential hub genes associated with immune cells' infiltration and the function of proinflammation, especially adipose tissue macrophages, in the progression of obesity-induced diabetes or insulin-resistance.", "claims": [{"id": "claim-method", "statement": "The “limma” package in R software (R Studio) was used to integrate and standardize the downloaded GEO expression chip to analyze the differentially expressed genes and their expression levels [21, 22].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33564304", "locator": "sections[6] \"2.4. Analysis of Differentially Expressed Genes\" paragraph 2", "quote": "The “limma” package in R software (R Studio) was used to integrate and standardize the downloaded GEO expression chip to analyze the differentially expressed genes and their expression levels [21, 22]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support this study will be made available from the corresponding author upon request (1931136@tongji.edu.cn).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33564304", "locator": "sections[27] \"Data Availability\" paragraph 2", "quote": "The data used to support this study will be made available from the corresponding author upon request (1931136@tongji.edu.cn)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33564304"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE26637"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE26637"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33564304", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2021/8820089", "sha256": 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(1931136@tongji.edu.cn).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data used to support this study will be made available from the corresponding author upon request (1931136@tongji.edu.cn).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM655603", "GSM655604", "GSM655605", "GSM655606", "GSM655607", "GSM655608", "GSM655609", "GSM655610", "GSM655611", "GSM655612", "GSM655613", "GSM655614", "GSM655615", "GSM655616", "GSM655617", "GSM655618", "GSM655619", "GSM655620", "GSM655621", "GSM655622"], "sample_count": 20, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Adipose tissue transcriptome in insulin resistance", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE27951", "role": "raw", "format": 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METHODS: Gene Expr", "re (22 °C–25 °C). At 8 weeks of age, 14 male mice were randomly divided into 2 groups and fed for 1", "7). The food intake and body weight of each mouse were recorded weekly. After 12 weeks, we per", "we performed glucose tolerance tests of each mouse. Blood glucose concentrations (mg/dl) were m"], "order_basis": "paper_text_order:650", "id": "assay:1"}, {"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ied the predicted hub genes by performing RT qPCR analysis in animals and human samples. Besid", "able 2: summary of primer sequences used for RT-qPCR. Supplemental Table 3: 30 commonly expressed", "e 2: summary of primer sequences used for RT-qPCR. Supplemental Table 3: 30 commonly expressed"], "order_basis": "paper_text_order:1320", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ub genes and immune cells. And, we performed immunohistochemistry and immunofluorescence analysis to verify th", ". And, we performed immunohistochemistry and immunofluorescence analysis to verify that the hub genes were a", "fraction in AT of IRO was verified by IF or IHC analysis. 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